/**
 * Copyright 2012 Brigham Young University
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *    http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
package edu.byu.nlp.cluster.mom;

import edu.byu.nlp.cluster.em.AlternatingEMAble;
import edu.byu.nlp.cluster.em.ClusteringAndPredictiveModels;
import edu.byu.nlp.cluster.em.Expectable;

/**
 * @author rah67
 *
 */
public class VariationalBayesAltEMAble implements AlternatingEMAble<HyperParams, MoMParameters> {

	private final boolean isHard;
	private final double temp;
	
	public VariationalBayesAltEMAble(boolean isHard, double temp) {
		this.isHard = isHard;
		this.temp = temp;
	}

	/** {@inheritDoc} */
	@Override
	public Expectable<MoMParameters> expectableForHyperParameters(HyperParams hyperParams) {
		return new VariationalBayesExpectable(hyperParams, isHard, temp);
	}

	/** {@inheritDoc} */
	@Override
	public ClusteringAndPredictiveModels newModelsFrom(MoMParameters parameters) {
		// FIXME : to build a predictive model we actually need a and b, which are not recoverable from the
		// parameters. This will probably require changes to interfaces.
		return ClusteringAndPredictiveModels.fromSingleModel(
				MixtureOfMultinomialsModel.newWithParameters(parameters, false));
	}

}
